The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are ...The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are computationally expensive and scarce.We propose a novel hyper-gradient type method with a warm-start strategy to address this challenge.Particularly,we first use a Taylor expansion-based approach to obtain a good initial point.Then we apply a hyper-gradient descent method with an ex-plicit approximate hyper-gradient.We establish the convergence results of our algorithm theoretically.Furthermore,when the follower employs the least squares loss function,our method is shown to reach an e-stationary point by solving quadratic subproblems.Numerical experiments show our algorithms are empirically orders of magnitude faster than the state-of-the-art.展开更多
The technology for beneficiation of banded iron ores containing low iron value is a challenging task due to increasing demand of quality iron ore in India. A flotation process has been developed to treat one such ore,...The technology for beneficiation of banded iron ores containing low iron value is a challenging task due to increasing demand of quality iron ore in India. A flotation process has been developed to treat one such ore, namely banded hematite quartzite （BHQ） containing 41.8wt% Fe and 41.5wt% SiO2,by using oleic acid, methyl isobutyl carbinol （MIBC）, and sodium silicate as the collector, frother, and dispersant, respectively. The relative effects of these variables have been evaluated in half-normal plots and Pareto charts using central composite rotatable design. A quadratic response model has been developed for both Fe grade and recovery and optimized within the experimental range. The optimum reagent dosages are found to be as follows： collector concentration of 243.58 g/t, dispersant concentration of 195.67 g/t, pH 8.69, and conditioning time of 4.8 min to achieve the maximum Fe grade of 64.25% with 67.33% recovery. The predictions of the model with regard to iron grade and recovery are in good agreement with the experimental results.展开更多
Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance un...Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle（UAV）. In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained.展开更多
In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of u...In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.展开更多
Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a ...Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras＇ parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion （DLT）, GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation.展开更多
A scheme to enhance near-infrared band absorption of a Si nanoparticle by placing the Si nanoparticle into a designed gold nanostructure is proposed. Three-dimensional （3D） finite-difference time-domain simulations ...A scheme to enhance near-infrared band absorption of a Si nanoparticle by placing the Si nanoparticle into a designed gold nanostructure is proposed. Three-dimensional （3D） finite-difference time-domain simulations are employed to calcu- late the absorption spectrum of the Si nanostructure and maximize it by generating alternate designs. The results show that in the near-infrared region over 700 nm, the absorption of a pure Si nanoparticle is very low, but when the same nanoparticle is placed within an optimally designed gold nanostructure, its absorption cross section can be enhanced by more than two orders of magnitude in the near-infrared band.展开更多
This paper investigates the use of the method of inequalities （MoI） to design output-feedback compensators for the problem of the control of instabilities in a laminar plane Poiseuille flow. In common with many flow...This paper investigates the use of the method of inequalities （MoI） to design output-feedback compensators for the problem of the control of instabilities in a laminar plane Poiseuille flow. In common with many flows, the dynamics of streamwise vortices in plane Poiseuille flow are very non-normal. Consequently, small perturbations grow rapidly with a large transient that may trigger nonlinearities and lead to turbulence even though such perturbations would, in a linear flow model, eventually decay. Such a system can be described as a conditionally linear system. The sensitivity is measured using the maximum transient energy growth, which is widely used in the fluid dynamics community. The paper considers two approaches. In the first approach, the MoI is used to design low-order proportional and proportional-integral （PI） controllers. In the second one, the MoI is combined with McFarlane and Glover＇s H∞ loop-shaping design procedure in a mixed-optimization approach.展开更多
This study aims to solve the problem of multi-missile simultaneous attacks on maneuvering target.The challenges include multimissile cooperative control and target's trajectory prediction.A controller based on non...This study aims to solve the problem of multi-missile simultaneous attacks on maneuvering target.The challenges include multimissile cooperative control and target's trajectory prediction.A controller based on nonlinear distributed model predictive control(NDMPC)is designed for multiple missiles against a maneuvering target,and a trajectory prediction inethod based on particle swarm optimization(PSO)algorithm is proposed.This study has mainly completed the following three aspects of work.Firstly,the cost function of the cont roller is constructed to optimize the accuracy and synchronization of the multi-missile system with consideration of collision avoidance.Secondly,the velocity control of the leading missile is designed by using the range-to-go in-formation in real time to ensure the attack fficiency and the control of the terminal velocity difference.Finally,a kinematic model of the target is cstimated by using short-term real-time data with the PSO algorithm.The established model is employed to predict the target trajectory in the interval between radar scans.Numerical simulation results of two different s enarios demonstrate the effectiveness of the proposed cooperative guidance approach.展开更多
Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation ...Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) and cloning process. This paper presents Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique in solving economic load dispatch problem. The combination creates a new algorithm that will be termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT). DEIANT was utilized to optimize economic load dispatch problem. A comparison was made between DEIANT and classical ACO to evaluate the performance of the new algorithm. In realizing the effectiveness of the proposed technique, IEEE 57-Bus Reliable Test System (RTS) has been used as the test specimen. Results obtained from the study revealed that the proposed DEIANT has superior computation time.展开更多
The lowest order Pl-nonconforming triangular finite element method （FEM） for elliptic and parabolic interface problems is investigated. Under some reasonable regularity assumptions on the exact solutions, the optima...The lowest order Pl-nonconforming triangular finite element method （FEM） for elliptic and parabolic interface problems is investigated. Under some reasonable regularity assumptions on the exact solutions, the optimal order error estimates are obtained in the broken energy norm. Finally, some numerical results are provided to verify the theoretical analysis.展开更多
We present an optimal control model of three stages of resources allocation for managing invasive species. Three types of temporal uncertainty are considered, involving the timing of discovery of an invasive pest, the...We present an optimal control model of three stages of resources allocation for managing invasive species. Three types of temporal uncertainty are considered, involving the timing of discovery of an invasive pest, the timing of an induced technology development after the establishment and dispersion of an invasive species, and the timing of farmer adoption of induced technology as the costs of controlling the invasive species increase. Using a bioeconomic optimal control model of managing invasive species, where models in previous studies are subset within our model, we show that when sub-structured models not including all three stages are used for managing invasive species, resource allocation for adopting preventive measures before the initial discovery of an invasive pest would be supra-optimalwhile resource allocation for adopting conventional control measures after establishment and dispersion would be sub-optimal.展开更多
Background:Schistosomiasis is a parasitic disease.It is caused by a prevalent infection in tropical areas and is transmitted through contaminated water with larvae parasites.Schistosomiasis is the second most parasiti...Background:Schistosomiasis is a parasitic disease.It is caused by a prevalent infection in tropical areas and is transmitted through contaminated water with larvae parasites.Schistosomiasis is the second most parasitic disease globally,so investigating its prevention and treatment is crucial.Methods:This paper aims to suggest a time-fractional model of schistosomiasis disease(T-FMSD)in the sense of the Caputo operator.The T-FMSD considers the dynamics involving susceptible ones not infected with schistosomiasis(S_(h)(t)),those infected with the infection(Ih(t)),those recovering from the disease(R(t)),susceptible snails with and without schistosomiasis infection,respectively shown by I_(v)(t)and S_(v)(t).We use a new basis function,generalized Bernoulli polynomials,for the approximate solution of T-FMSD.The operational matrices are incorporated into the method of Lagrange multipliers so that the fractional problem can be transformed into an algebraic system of equations.Results:The existence and uniqueness of the solution,and the convergence analysis of the model are established.The numerical computations are graphically presented to depict the variations of the compartments with time for varied fractional order derivatives.Conclusions:The proposed method not only provides an accurate solution but also can accurately predict schistosomiasis transmission.The results of this study will assist medical scientists in taking necessary measures during screening and treatment processes.展开更多
In this paper, two PVD-type algorithms are proposed for solving inseparable linear constraint optimization. Instead of computing the residual gradient function, the new algorithm uses the reduced gradients to construc...In this paper, two PVD-type algorithms are proposed for solving inseparable linear constraint optimization. Instead of computing the residual gradient function, the new algorithm uses the reduced gradients to construct the PVD directions in parallel computation, which can greatly reduce the computation amount each iteration and is closer to practical applications for solve large-scale nonlinear programming. Moreover, based on an active set computed by the coordinate rotation at each iteration, a feasible descent direction can be easily obtained by the extended reduced gradient method. The direction is then used as the PVD direction and a new PVD algorithm is proposed for the general linearly constrained optimization. And the global convergence is also proved.展开更多
文摘The Stackelberg prediction game(SPG)is a bilevel optimization frame-work for modeling strategic interactions between a learner and a follower.Existing meth-ods for solving this problem with general loss functions are computationally expensive and scarce.We propose a novel hyper-gradient type method with a warm-start strategy to address this challenge.Particularly,we first use a Taylor expansion-based approach to obtain a good initial point.Then we apply a hyper-gradient descent method with an ex-plicit approximate hyper-gradient.We establish the convergence results of our algorithm theoretically.Furthermore,when the follower employs the least squares loss function,our method is shown to reach an e-stationary point by solving quadratic subproblems.Numerical experiments show our algorithms are empirically orders of magnitude faster than the state-of-the-art.
文摘The technology for beneficiation of banded iron ores containing low iron value is a challenging task due to increasing demand of quality iron ore in India. A flotation process has been developed to treat one such ore, namely banded hematite quartzite （BHQ） containing 41.8wt% Fe and 41.5wt% SiO2,by using oleic acid, methyl isobutyl carbinol （MIBC）, and sodium silicate as the collector, frother, and dispersant, respectively. The relative effects of these variables have been evaluated in half-normal plots and Pareto charts using central composite rotatable design. A quadratic response model has been developed for both Fe grade and recovery and optimized within the experimental range. The optimum reagent dosages are found to be as follows： collector concentration of 243.58 g/t, dispersant concentration of 195.67 g/t, pH 8.69, and conditioning time of 4.8 min to achieve the maximum Fe grade of 64.25% with 67.33% recovery. The predictions of the model with regard to iron grade and recovery are in good agreement with the experimental results.
文摘Evolutionary algorithm is time-consuming because of the large number of evolutions and much times of finite element analysis, when it is used to optimize the wing structure of a certain high altitude long endurance unmanned aviation vehicle（UAV）. In order to improve efficiency it is proposed to construct a model management framework to perform the multi-objective optimization design of wing structure. The sufficient accurate approximation models of objective and constraint functions in the wing structure optimization model are built when using the model management framework, therefore in the evolutionary algorithm a number of finite element analyses can he avoided and the satisfactory multi-objective optimization results of the wing structure of the high altitude long endurance UAV are obtained.
基金supported in part by Shanghai Pujiang Program under Grant No.21PJ1402600in part by Natural Science Foundation of Chongqing,China under Grant No.CSTB2022NSCQ-MSX0375+4 种基金in part by Song Shan Laboratory Foundation,under Grant No.YYJC022022007in part by Zhejiang Provincial Natural Science Foundation of China under Grant LGJ22F010001in part by National Key Research and Development Program of China under Grant 2020YFA0711301in part by National Natural Science Foundation of China under Grant 61922049。
文摘In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.
文摘Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras＇ parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion （DLT）, GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation.
基金Project supported by the National Key Basic Research and Development Program of China(Grant No.2013CB632704)the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.Y1 V2013L11)
文摘A scheme to enhance near-infrared band absorption of a Si nanoparticle by placing the Si nanoparticle into a designed gold nanostructure is proposed. Three-dimensional （3D） finite-difference time-domain simulations are employed to calcu- late the absorption spectrum of the Si nanostructure and maximize it by generating alternate designs. The results show that in the near-infrared region over 700 nm, the absorption of a pure Si nanoparticle is very low, but when the same nanoparticle is placed within an optimally designed gold nanostructure, its absorption cross section can be enhanced by more than two orders of magnitude in the near-infrared band.
文摘This paper investigates the use of the method of inequalities （MoI） to design output-feedback compensators for the problem of the control of instabilities in a laminar plane Poiseuille flow. In common with many flows, the dynamics of streamwise vortices in plane Poiseuille flow are very non-normal. Consequently, small perturbations grow rapidly with a large transient that may trigger nonlinearities and lead to turbulence even though such perturbations would, in a linear flow model, eventually decay. Such a system can be described as a conditionally linear system. The sensitivity is measured using the maximum transient energy growth, which is widely used in the fluid dynamics community. The paper considers two approaches. In the first approach, the MoI is used to design low-order proportional and proportional-integral （PI） controllers. In the second one, the MoI is combined with McFarlane and Glover＇s H∞ loop-shaping design procedure in a mixed-optimization approach.
文摘This study aims to solve the problem of multi-missile simultaneous attacks on maneuvering target.The challenges include multimissile cooperative control and target's trajectory prediction.A controller based on nonlinear distributed model predictive control(NDMPC)is designed for multiple missiles against a maneuvering target,and a trajectory prediction inethod based on particle swarm optimization(PSO)algorithm is proposed.This study has mainly completed the following three aspects of work.Firstly,the cost function of the cont roller is constructed to optimize the accuracy and synchronization of the multi-missile system with consideration of collision avoidance.Secondly,the velocity control of the leading missile is designed by using the range-to-go in-formation in real time to ensure the attack fficiency and the control of the terminal velocity difference.Finally,a kinematic model of the target is cstimated by using short-term real-time data with the PSO algorithm.The established model is employed to predict the target trajectory in the interval between radar scans.Numerical simulation results of two different s enarios demonstrate the effectiveness of the proposed cooperative guidance approach.
文摘Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) and cloning process. This paper presents Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique in solving economic load dispatch problem. The combination creates a new algorithm that will be termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT). DEIANT was utilized to optimize economic load dispatch problem. A comparison was made between DEIANT and classical ACO to evaluate the performance of the new algorithm. In realizing the effectiveness of the proposed technique, IEEE 57-Bus Reliable Test System (RTS) has been used as the test specimen. Results obtained from the study revealed that the proposed DEIANT has superior computation time.
基金Project supported by the National Natural Science Foundation of China(No.11271340)
文摘The lowest order Pl-nonconforming triangular finite element method （FEM） for elliptic and parabolic interface problems is investigated. Under some reasonable regularity assumptions on the exact solutions, the optimal order error estimates are obtained in the broken energy norm. Finally, some numerical results are provided to verify the theoretical analysis.
文摘We present an optimal control model of three stages of resources allocation for managing invasive species. Three types of temporal uncertainty are considered, involving the timing of discovery of an invasive pest, the timing of an induced technology development after the establishment and dispersion of an invasive species, and the timing of farmer adoption of induced technology as the costs of controlling the invasive species increase. Using a bioeconomic optimal control model of managing invasive species, where models in previous studies are subset within our model, we show that when sub-structured models not including all three stages are used for managing invasive species, resource allocation for adopting preventive measures before the initial discovery of an invasive pest would be supra-optimalwhile resource allocation for adopting conventional control measures after establishment and dispersion would be sub-optimal.
文摘Background:Schistosomiasis is a parasitic disease.It is caused by a prevalent infection in tropical areas and is transmitted through contaminated water with larvae parasites.Schistosomiasis is the second most parasitic disease globally,so investigating its prevention and treatment is crucial.Methods:This paper aims to suggest a time-fractional model of schistosomiasis disease(T-FMSD)in the sense of the Caputo operator.The T-FMSD considers the dynamics involving susceptible ones not infected with schistosomiasis(S_(h)(t)),those infected with the infection(Ih(t)),those recovering from the disease(R(t)),susceptible snails with and without schistosomiasis infection,respectively shown by I_(v)(t)and S_(v)(t).We use a new basis function,generalized Bernoulli polynomials,for the approximate solution of T-FMSD.The operational matrices are incorporated into the method of Lagrange multipliers so that the fractional problem can be transformed into an algebraic system of equations.Results:The existence and uniqueness of the solution,and the convergence analysis of the model are established.The numerical computations are graphically presented to depict the variations of the compartments with time for varied fractional order derivatives.Conclusions:The proposed method not only provides an accurate solution but also can accurately predict schistosomiasis transmission.The results of this study will assist medical scientists in taking necessary measures during screening and treatment processes.
基金Supported by the National Natural Science Foundation of China(No.11101420,11331012,71271204)
文摘In this paper, two PVD-type algorithms are proposed for solving inseparable linear constraint optimization. Instead of computing the residual gradient function, the new algorithm uses the reduced gradients to construct the PVD directions in parallel computation, which can greatly reduce the computation amount each iteration and is closer to practical applications for solve large-scale nonlinear programming. Moreover, based on an active set computed by the coordinate rotation at each iteration, a feasible descent direction can be easily obtained by the extended reduced gradient method. The direction is then used as the PVD direction and a new PVD algorithm is proposed for the general linearly constrained optimization. And the global convergence is also proved.
